How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality. But empirical measures of both inequality and mobility tend to be biased upward due to measurement error in income and expenditure data collected from household surveys. This paper examines how to reduce or remove this bias using instrumental variable methods, and provides conditions that instrumental variables must satisfy to provide consistent estimates. This approach is applied to panel data from Vietnam. The results imply that at least 15 percent, and perhaps as much as 42 percent, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12 percent of measured inequality.
Saved in:
| Main Author: | |
|---|---|
| Format: | Journal Article biblioteca |
| Language: | en_US |
| Published: |
Oxford University Press on behalf of the World Bank
2012-06-01
|
| Subjects: | autocorrelation, covariance, Econometrics, economic growth, equations, functional forms, household surveys, Hypotheses, income, independent variables, inequality, instrumental variables, long-run inequality, matrices, Matrix, Measurement Error, measurement errors, Sample size, standard deviations, standard errors, |
| Online Access: | http://hdl.handle.net/10986/16351 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
dig-okr-1098616351 |
|---|---|
| record_format |
koha |
| spelling |
dig-okr-10986163512021-04-23T14:03:28Z How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam Glewwe, Paul autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality. But empirical measures of both inequality and mobility tend to be biased upward due to measurement error in income and expenditure data collected from household surveys. This paper examines how to reduce or remove this bias using instrumental variable methods, and provides conditions that instrumental variables must satisfy to provide consistent estimates. This approach is applied to panel data from Vietnam. The results imply that at least 15 percent, and perhaps as much as 42 percent, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12 percent of measured inequality. 2013-12-04T17:40:37Z 2013-12-04T17:40:37Z 2012-06-01 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/16351 en_US CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Oxford University Press on behalf of the World Bank Journal Article Vietnam |
| institution |
Banco Mundial |
| collection |
DSpace |
| country |
Estados Unidos |
| countrycode |
US |
| component |
Bibliográfico |
| access |
En linea |
| databasecode |
dig-okr |
| tag |
biblioteca |
| region |
America del Norte |
| libraryname |
Biblioteca del Banco Mundial |
| language |
en_US |
| topic |
autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors |
| spellingShingle |
autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors Glewwe, Paul How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| description |
Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality. But empirical measures of both inequality and mobility tend to be biased upward due to measurement error in income and expenditure data collected from household surveys. This paper examines how to reduce or remove this bias using instrumental variable methods, and provides conditions that instrumental variables must satisfy to provide consistent estimates. This approach is applied to panel data from Vietnam. The results imply that at least 15 percent, and perhaps as much as 42 percent, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12 percent of measured inequality. |
| format |
Journal Article |
| topic_facet |
autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors |
| author |
Glewwe, Paul |
| author_facet |
Glewwe, Paul |
| author_sort |
Glewwe, Paul |
| title |
How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| title_short |
How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| title_full |
How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| title_fullStr |
How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| title_full_unstemmed |
How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam |
| title_sort |
how much of observed economic mobility is measurement error? iv methods to reduce measurement error bias, with an application to vietnam |
| publisher |
Oxford University Press on behalf of the World Bank |
| publishDate |
2012-06-01 |
| url |
http://hdl.handle.net/10986/16351 |
| work_keys_str_mv |
AT glewwepaul howmuchofobservedeconomicmobilityismeasurementerrorivmethodstoreducemeasurementerrorbiaswithanapplicationtovietnam |
| _version_ |
1756573162817978368 |